A company stores web server logs in a Delta Lake table. The table is partitioned by `date` and `hour`. Queries often filter on `ip_address` and `url`. The team wants to improve query performance. What should they do?

Disable statistics collection for `ip_address` and `url`

Z-order by `ip_address` and `url`

Increase the number of files by lowering the target file size

What is the default behavior of Delta Lake when a write operation attempts to add a new column to an existing table?

The write succeeds and the new column is added automatically

The write succeeds but the new column is ignored

The write succeeds but the table becomes corrupted

The write fails because schema enforcement is on by default

A team runs concurrent streaming jobs that write to the same Delta Lake table. Occasionally, they encounter conflicts where one job fails due to concurrent writes. They want to reduce the likelihood of conflicts while maintaining data consistency. What should they configure?

Set `spark.databricks.delta.commitInfo.enabled` to false

Set `spark.databricks.delta.isolationLevel` to `Serializable`

Use `OPTIMIZE` with `ZORDER BY` to reduce write conflicts

Partition the table on a column that distributes writes evenly

A Delta Lake table currently has columns `id`, `name`, and `age`. A new data source includes an additional column `email`. Which approach allows the table to accept this new column without failing the write?

Drop the `email` column from the DataFrame before writing

Enable schema evolution on the write operation

Use `VACUUM` to clean the schema

DatabricksCertified Data Engineer Professional

Domain 10Objective 1

Design and Implement Scalable Data Models Using Delta Lake to Manage Large Datasets. DATA-ENGINEER-PROFESSIONAL Practice Questions (Page 5)

Part of the Data Modeling domain, which accounts for 6% of the DATA-ENGINEER-PROFESSIONAL exam. Databricks does not publish an official question count, but from its 120-minute exam (~50–80 total, ~3–5 in this domain), expect 1–1 from this objective — we provide 29 practice questions to prepare you well beyond it. (estimate)

29questions here

6free pages

7concepts

6%of the exam

Questions 21–25

21application · medium
A company stores web server logs in a Delta Lake table. The table is partitioned by `date` and `hour`. Queries often filter on `ip_address` and `url`. The team wants to improve query performance. What should they do?
Select an answer first
22foundation · easy
What is the default behavior of Delta Lake when a write operation attempts to add a new column to an existing table?
Select an answer first
23foundation · easy
A data engineer needs to regularly clean up old versions of a Delta Lake table to reduce storage costs. Which command should be scheduled as part of a maintenance routine?
Select an answer first
24application · medium
A team runs concurrent streaming jobs that write to the same Delta Lake table. Occasionally, they encounter conflicts where one job fails due to concurrent writes. They want to reduce the likelihood of conflicts while maintaining data consistency. What should they configure?
Select an answer first
25foundation · easy
A Delta Lake table currently has columns `id`, `name`, and `age`. A new data source includes an additional column `email`. Which approach allows the table to accept this new column without failing the write?
Select an answer first

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